Review of Canadian Experience With the Fabrication of Thoria-Based Fuels for Advanced Reactors and Fuel Cycles for Long-Term Nuclear Energy Sustainability and Security
Bibliographic record
Abstract
Abstract Advanced fuels and fuel cycles are important for the current and next generation of advanced reactors, small modular reactors, and microreactors, in order to maximize the utilization of fissile and fertile nuclear fuel resources, and also to minimize the mass and volume of radioactive waste to be placed into long-term storage. Thorium-based fuels are a potentially attractive option for both advanced fuels and fuel cycles, since neutron irradiation will lead to the conversion of fertile 232Th to fissile 233U. Thus, thorium-based fuels can be used to augment and extend uranium resources. Through work done at Canadian Nuclear Laboratories (CNL), Canada has gained extensive experience over more than 50 years of how to fabricate thorium-based fuels. This paper provides an overview of Canada's experience in the fabrication of thorium-based fuels (mainly ThO2, (Th,U)O2, and (Th,Pu)O2) at CNL at its Chalk River Laboratories (CRL). Thoria (ThO2) fuel pellet fabrication uses processes and equipment similar to that of uranium dioxide (UO2) fuel pellet fabrication. However, since thorium lacks a fissile isotope, most ThO2 pellet fabrication processes must include a step to add a fissile component, such as enriched UO2, plutonium dioxide (PuO2), or U-233 in the form of 233UO2. Along with a review of the fuel fabrication effort that has taken place at CNL, the potential impact that CNL's extensive experience with thoria fabrication could have on the future Canadian nuclear energy landscape is also discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".